"If the audience can see all the charts at once, they may get a different story from the one you want them to get. Show the charts one at a time. If you have only one chart, keep it covered until you are ready to use it. Take full advantage of the element of surprise. If you use charts which open like a book, use only one page for the message." (Edward J Hegarty, "How to Use a Set of Display Charts", The American Statistician Vol. 2 (5), 1948)
"In making up the charts, keep them simple. One idea to a page and not too much detail is a good rule. Try to get variety in the subject matter - now a chart, next a diagram, then a tabulation. Such variety helps hold audience attention." (Edward J Hegarty, "How to Use a Set of Display Charts", The American Statistician Vol. 2 (5), 1948)
"Try telling the story in words different from those on the charts. […] If the chart shows a picture, describe the picture. Tell what it shows and why it is shown. If it is a diagram, explain it. Don't leave the audience to figure it out. No matter how simple the story shown, tell it in your own words: but remember that explaining a chart doesn't mean reading it out loud." (Edward J Hegarty, "How to Use a Set of Display Charts", The American Statistician Vol. 2 (5), 1948)
"Recognize effective results. Does the type of chart selected give a comprehensive picture of the situation? Does the size of chart and visual aid used satisfy all audience requirements? Do materials meet all reproduction problems? Is the layout well balanced and style of lettering uniform? Does the chart as a whole accurately present the facts? Is the projected idea an effective visual tool?" (Mary E Spear, "Charting Statistics", 1952)
"Understandability implies that the graph will mean something to the audience. If the presentation has little meaning to the audience, it has little value. Understandability is the difference between data and information. Data are facts. Information is facts that mean something and make a difference to whoever receives them. Graphic presentation enhances understanding in a number of ways. Many people find that the visual comparison and contrast of information permit relationships to be grasped more easily. Relationships that had been obscure become clear and provide new insights." (Anker V Andersen, "Graphing Financial Information: How accountants can use graphs to communicate", 1983)
"The conditions under which many data graphics are produced - the lack of substantive and quantitative skills of the illustrators, dislike of quantitative evidence, and contempt for the intelligence of the audience-guarantee graphic mediocrity. These conditions engender graphics that (1) lie; (2) employ only the simplest designs, often unstandardized time-series based on a small handful of data points; and (3) miss the real news actually in the data." (Edward R Tufte, "The Visual Display of Quantitative Information", 1983)
"Lurking behind chartjunk is contempt both for information and for the audience. Chartjunk promoters imagine that numbers and details are boring, dull, and tedious, requiring ornament to enliven. Cosmetic decoration, which frequently distorts the data, will never salvage an underlying lack of content. If the numbers are boring, then you've got the wrong numbers." (Edward R Tufte, "Envisioning Information", 1990)
"Audience boredom is usually a content failure, not a decoration failure." (Edward R Tufte, "The cognitive style of PowerPoint", 2003)
"If you want to hide data, try putting it into a larger group and then use the average of the group for the chart. The basis of the deceit is the endearingly innocent assumption on the part of your readers that you have been scrupulous in using a representative average: one from which individual values do not deviate all that much. In scientific or statistical circles, where audiences tend to take less on trust, the 'quality' of the average" (in terms of the scatter of the underlying individual figures) is described by the standard deviation, although this figure is itself an average." (Nicholas Strange, "Smoke and Mirrors: How to bend facts and figures to your advantage", 2007)
"Information consumption can lead to higher knowledge on the part of the audience, if its members are able to perceive the patterns or meaning of data. It is not a passive process; our brains are not hard drives that store stuff uncritically .When people see, read, or listen, they assimilate content by relating it to their memories and experiences." (Alberto Cairo, "The Functional Art", 2011)
"The more adequately a model fits whatever it stands for without being needlessly complex, and the easier it is for its intended audience to interpret it correctly, the better it will be." (Alberto Cairo, "The Functional Art", 2011)
"An infographic (short for information graphic) is a type of picture that blends data with design, helping individuals and organizations concisely communicate messages to their audience." (Mark Smiciklas, "The Power of Infographics: Using Pictures to Communicate and Connect with Your Audiences", 2012)
"Competition for your audiences attention is fierce. The fact that infographics are unique allows organizations an opportunity to make the content they are publishing stand out and get noticed." (Mark Smiciklas, "The Power of Inforgraphics", 2012)
"Most important, the range of data literacy and familiarity with your data’s context is much wider when you design graphics for a general audience." (Nathan Yau, "Data Points: Visualization That Means Something", 2013)
"Any presentation of data, whether a simple calculated metric or a complex predictive model, is going to have a set of assumptions and choices that the producer has made to get to the output. The more that these can be made explicit, the more the audience of the data will be open to accepting the message offered by the presenter." (Zach Gemignani et al, "Data Fluency", 2014)
"In fact, the analogy to storytelling is limited when applied to communicating with data. Data visualization has fundamental characteristics missing from traditional storytelling. For example, interactive data visualizations let audiences explore information to find insights that resonate with them. Visualizations take shape based to a large extent on the underlying data. And as this data changes, the emphasis and message of the visualization is likely to change." (Zach Gemignani et al, "Data Fluency", 2014)
Beyond annoying our audience by trying to sound smart, we run the risk of making our audience feel dumb. In either case, this is not a good user experience for our audience." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)
"First, to whom are you communicating? It is important to have a good understanding of who your audience is and how they perceive you. This can help you to identify common ground that will help you ensure they hear your message. Second, What do you want your audience to know or do?" (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)
"If you simply present data, it’s easy for your audience to say, Oh, that’s interesting, and move on to the next thing. But if you ask for action, your audience has to make a decision whether to comply or not. This elicits a more productive reaction from your audience, which can lead to a more productive conversation - one that might never have been started if you hadn’t recommended the action in the first place." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)
"Tailoring the message to the audience should not be synonymous with accepting its prejudices, routines, and the usual ways of doing things. Many of what we believe to be good data visualization principles are opposite to what is practiced within organizations. When presenting a chart type the audience is unfamiliar with, or when breaking a rule, the author must argue for its advantages. Annotating the chart, showing how to read it, drawing aˆention to key points, and making direct comparisons with alternative representations will help the audience feel safer in their reading and possible adoption of the new chart." (Jorge Camões, "Data at Work: Best practices for creating effective charts and information graphics in Microsoft Excel", 2016)
"Data analysis is more than crunching numbers; it is about finding insights, identifying the unknown unknowns, and presenting the data in a simple yet deep enough way so that your audience can understand your insights and make decisions." (Andy Kriebel & Eva Murray, "#MakeoverMonday: Improving How We Visualize and Analyze Data, One Chart at a Time", 2018)
"Ideally, the charts are designed in a way that gives your audience clarity and lets them understand the key insights very quickly. Color choices, highlighting, annotations, and other ways of drawing attention to your findings help in the process. By leaving white or blank space around your charts, you are able to keep the focus of your audience on the key message rather than distracting or confusing them." (Andy Kriebel & Eva Murray, "#MakeoverMonday: Improving How We Visualize and Analyze Data, One Chart at a Time", 2018)
"Data storytelling is transformative. Many people don’t realize that when they share insights, they’re not just imparting information to other people. The natural consequence of sharing an insight is change. Stop doing that, and do more of this. Focus less on them, and concentrate more on these people. Spend less there, and invest more here. A poignant insight will drive an enlightened audience to think or act differently. So, as a data storyteller, you’re not only guiding the audience through the data, you’re also acting as a change agent. Rather than just pointing out possible enhancements, you’re helping your audience fully understand the urgency of the changes and giving them the confidence to move forward." (Brent Dykes, "Effective Data Storytelling: How to Drive Change with Data, Narrative and Visuals", 2019)
"The first rule of communication is to shut up and listen, so that you can get to know about the audience for your communication, whether it might be politicians, professionals or the general public. We have to understand their inevitable limitations and any misunderstandings, and fight the temptation to be too sophisticated and clever, or put in too much detail." (David Spiegelhalter, "The Art of Statistics: Learning from Data", 2019)
"There are eight audience considerations that can influence how you approach your data story: (1) Key goals and priorities. [...] (2) Beliefs and preferences. [...] (3) Specific expectations. [...] (4) Opportune timing. [...] (5) Topic familiarity. [...] (6) Data literacy. [...] (7) Seniority level. [...] (8) Audience mix." (Brent Dykes, "Effective Data Storytelling: How to Drive Change with Data, Narrative and Visuals", 2019)
"There is often no one 'best' visualization, because it depends on context, what your audience already knows, how numerate or scientifically trained they are, what formats and conventions are regarded as standard in the particular field you’re working in, the medium you can use, and so on. It’s also partly scientific and partly artistic, so you get to express your own design style in it, which is what makes it so fascinating." (Robert Grant, "Data Visualization: Charts, Maps and Interactive Graphics", 2019)
"As presenters of data visualizations, often we just want our audience to understand something about their environment – a trend, a pattern, a breakdown, a way in which things have been progressing. If we ask ourselves what we want our audience to do with that information, we might have a hard time coming up with a clear answer sometimes. We might just want them to know something." (Ben Jones, "Avoiding Data Pitfalls: How to Steer Clear of Common Blunders When Working with Data and Presenting Analysis and Visualizations", 2020)
"As data visualization creators, we must understand our audience and know when a different graph can engage readers - and help them expand their own graphic literacy." (Jonathan Schwabish, "Better Data Visualizations: A guide for scholars, researchers, and wonks", 2021)
"Data visualization‘s key responsibilities and challenges include the obligation to earn your audience’s attention - do not take it for granted." (Bill Inmon et al, "Building the Data Lakehouse", 2021)
"What is the secret to getting people to use charts and dashboards? Personalization. Inserting the audience into the visualization, and making it especially meaningful and relevant to the user, never fails." (Steve Wexler, "The Big Picture: How to use data visualization to make better decisions - faster", 2021)
"Design choices include more deliberate thought put into resizing, cropping, simplifying, and enhancing information within the limited real estate. These thumbnails need to be visually interpretable, yet inviting and engaging to the audience." (Vidya Setlur & Bridget Cogley, "Functional Aesthetics for data visualization", 2022)
"A perfectly relevant visualization that breaks a few presentation rules is far more valuable - it’s better - than a perfectly executed, beautiful chart that contains the wrong data, communicates the wrong message, or fails to engage its audience." (Scott Berinato, "Good Charts : the HBR guide to making smarter, more persuasive data visualizations", 2023)
"Data becomes more useful once it’s transformed into a data visualization or used in a data story. Data storytelling is the ability to effectively communicate insights from a dataset using narratives and visualizations. It can be used to put data insights into context and inspire action from your audience. Color can be very helpful when you are trying to make information stand out within your data visualizations." (Kate Strachnyi, "ColorWise: A Data Storyteller’s Guide to the Intentional Use of Color", 2023)
"Good design isn’t just choosing colors and fonts or coming up with an aesthetic for charts. That’s styling - part of design, but by no means the most important part. Rather, people with design talent develop and execute systems for effective visual communication. They understand how to create and edit visuals to focus an audience and distill ideas." (Scott Berinato, "Good Charts : the HBR guide to making smarter, more persuasive data visualizations", 2023)
"One tip to keep an audience focused on your story without overwhelming them is to reduce the saturation of the colors [...] When you lower the brightness and intensity, you are reducing the cognitive load that your audience has to bear. [...] Regardless of what combinations you decide on, you need to avoid pure colors that are bright and saturated." (Kate Strachnyi, "ColorWise: A Data Storyteller’s Guide to the Intentional Use of Color", 2023)
"Sketching bridges idea and visualization. Good sketches are quick, simple, and messy. Don’t think too much about real values or scales or any refining details. In fact, don’t think too much. Just keep in mind those keywords, the possible forms they suggest, and that overarching idea you keep coming back to, the one you wrote down in answer to 'What am I trying to say (or learn)?' And draw. Create shapes, develop a sense of what you want your audience to see. Try anything." (Scott Berinato, "Good Charts : the HBR guide to making smarter, more persuasive data visualizations", 2023)
